Sr Machine Learning Engineer

PayPal•San Jose, CA

4d•Hybrid

About The Position

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Requirements

3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
Several years of experience in designing, implementing, and deploying machine learning models.

Nice To Haves

Hands-on expertise with modern recommender architectures: two-tower retrieval, multi-task learning (MMoE, PLE), sequence/transformer models for user activity, and deep cross networks; fluent in PyTorch or TensorFlow
Experience building feed or home-screen ranking systems with multiple competing objectives (engagement, diversity, freshness, fairness) and low-latency serving (P99 < 100ms)
Production experience with graph neural networks (GraphSAGE, PinSage, LightGCN) or large-scale graph embeddings for social/interaction graphs — strongly preferred
Familiarity with contextual bandits, Thompson sampling, or RL for Next Best Action and notification problems
Strong ML systems fundamentals: distributed training, model serving, feature stores, and rigorous A/B testing
Prior work at a consumer social, marketplace, content, or fintech company (Meta, Pinterest, LinkedIn, YouTube, Snap, TikTok, Uber, DoorDash, Stripe, Block, Coinbase, or similar)
Clear technical communicator who can write design docs, influence cross-team decisions, and mentor engineers
PhD in CS, ML or related field strongly preferred; MS with strong industry depth also welcomed.
Publications at NeurIPS, ICML, KDD, RecSys, SIGIR, or WWW are a plus

Responsibilities

Develop and optimize machine learning models for various applications.
Preprocess and analyze large datasets to extract meaningful insights.
Deploy ML solutions into production environments using appropriate tools and frameworks.
Collaborate with cross-functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models.